Haiqu

My favorite page on Haiqu's documentation portal is our changelog. It is probably the best illustration of the product velocity we've been building over the past few months. We released the @Haiqu Platform in May, and five months later, we are already at SDK v1.7.0. and we just revealed Haiqu AgenticOS as a new pillar in our product system. I am impressed by how much it has evolved in such a short time. A few of my favorite additions (among many others): Hardware-topology-aware circuit compression for square and heavy-hex qubit grids used by IBM, IQM, and Google processors, helping reach impressive compression gains when problem circuits map to real hardware structure. Advanced data loading and state preparation, particularly important for financial applications such as derivatives pricing and anomaly detection. Quantum machine learning tools combining pretraining, variational optimization, circuit compression, error mitigation, and postprocessing. Flexible workflow orchestration, allowing researchers to combine and fine-tune circuit processing, optimization, execution, and mitigation stages. Advanced experiment control panel with circuit analytics, experiment tracking, sharing, and reproducibility. SKQD workflows in v1.7.0, combining quantum sampling with classical postprocessing for quantum simulation. What I find particularly exciting is that every new capability builds on infrastructure we have already developed. This makes it easier to turn every new R&D finding into a usable product. We now release new functionality weekly, incorporate some user requests within days, and often deliver urgent fixes on the same day. Explore our changelog: https://lnkd.in/d3wiPqRT

Missed our live walkthrough of Haiqu AgenticOS? The recording is now available. Together with Dikshant Dulal and Denise Ruffner, we demonstrated how to take a quantum research question into a structured, verifiable workflow that leads to a quantum prototype, while keeping scientists in control of the research process. If you're interested in using AI for advanced quantum research and algorithm development, you can register to access the recording here: https://lnkd.in/dpkiyHu6 For more information about Haiqu AgenticOS check https://haiqu.ai/agenticos

𝗝𝗼𝗶𝗻 𝗼𝘂𝗿 𝗹𝗶𝘃𝗲 𝘄𝗲𝗯𝗶𝗻𝗮𝗿 𝗳𝗼𝗿 𝗮𝗻 𝗶𝗻𝘀𝗶𝗱𝗲 𝗹𝗼𝗼𝗸 𝗮𝘁 𝗵𝗼𝘄 𝘆𝗼𝘂 𝗰𝗮𝗻 𝘂𝘀𝗲 𝗛𝗮𝗶𝗾𝘂 𝗔𝗴𝗲𝗻𝘁𝗶𝗰𝗢𝗦 𝘁𝗼 𝘀𝗽𝗲𝗲𝗱 𝘂𝗽 𝘆𝗼𝘂𝗿 𝗾𝘂𝗮𝗻𝘁𝘂𝗺 𝗿𝗲𝘀𝗲𝗮𝗿𝗰𝗵 Dikshant Dulal, Mykola Maksymenko and Denise Ruffner will show you how Haiqu AgenticOS: - Turns a research question into a structured graph. - Allows the researcher to review, give feedback and approvals - Runs experiments on quantum hardware through Haiqu’s software stack We’ll explore how AgenticOS helps shorten quantum R&D timelines from weeks to days using real examples from quantum chemistry, optimization, and many-body physics case studies. 📆 When: October 20, 2026 – 4 PM CET / 10 AM EST Register here: https://lnkd.in/eBiufSNs

We will never have enough quantum scientists to explore every promising quantum application. Talent is too scarce, and R&D takes too long. Developing a serious quantum application requires considerable expert time, from scientific problem formulation and algorithm design to numerical validation and hardware experiments. We built Haiqu AgenticOS to compress research cycles from weeks to days with dedicated teams of AI agents, while keeping scientists in control of the research process. On October 20, I'll join Dikshant Dulal and Denise Ruffner for a live walkthrough of the system, using real projects in quantum chemistry, optimization, and many-body physics. October 20 | 4 PM CEST / 10 AM EDT Register: https://lnkd.in/dpkiyHu6

𝗖𝘂𝗿𝗶𝗼𝘂𝘀 𝗵𝗼𝘄 𝗼𝘂𝗿 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝘀𝘆𝘀𝘁𝗲𝗺 𝗰𝗮𝗻 𝗵𝗲𝗹𝗽 𝘀𝗽𝗲𝗲𝗱 𝘂𝗽 𝘆𝗼𝘂𝗿 𝗿𝗲𝘀𝗲𝗮𝗿𝗰𝗵? 𝗖𝗼𝗺𝗲 𝗷𝗼𝗶𝗻 𝗼𝘂𝗿 𝘄𝗲𝗯𝗶𝗻𝗮𝗿. Dikshant Dulal, Mykola Maksymenko and Denise Ruffner will show you how Haiqu's AgenticOS: • Turns a research question into a structured graph. • Allows you to review, give feedback and approvals • Runs experiments on quantum hardware through Haiqu’s software stack They’ll cover how AgenticOS helps shorten quantum R&D timelines from weeks to days using real examples from quantum chemistry, optimization, and many-body physics case studies. 📆 𝗪𝗵𝗲𝗻: 𝗢𝗰𝘁𝗼𝗯𝗲𝗿 𝟮𝟬, 𝟮𝟬𝟮𝟲 – 𝟰 𝗣𝗠 𝗖𝗘𝗧 / 𝟭𝟬 𝗔𝗠 𝗘𝗦𝗧 𝗥𝗲𝗴𝗶𝘀𝘁𝗲𝗿 𝗵𝗲𝗿𝗲: https://lnkd.in/eNVJVP92

For years, we’ve focused on building better quantum computers. We also need to make it easier to do useful work with them. Haiqu’s new AgenticOS uses specialized AI agents to automate much of the quantum Research and Development workflow—from scientific modeling and simulation to hardware-ready circuits—while keeping researchers in control of the science. Haiqu is already demonstrating the approach in quantum chemistry and condensed matter physics, including a 75% reduction in circuit depth in one IBM hardware experiment. Making quantum R&D faster and more accessible is an important step toward practical use. Check it out: https://haiqu.ai/agenticos